EPPS 6356 Data Visualization Project

This storyboard delivers our final project product by visualizing Formula 1 Racing data focused on analyzing information on the drivers and different circuits.

Data showcase 1: Circuit Data


Different drivers’ race win records across various circuits are presented here. The legend on the bottom lists the circuits in the data set and then the bar chart visualizes the number of wins for each driver.

Data showcase 2: Which factors are important to determine the best driver?


Multiple linear regression was utilized to determine which factors are important to evaluate the best driver.

Wins = b0 + (Pole Wins) X1 + (Total Points) X2 + (Fastest Laps) X3 + (Podiums) X4 + e
Note: b0 is the intercept of the regression line and e is the model error (residuals) or the variation in the model

R^2 = 0.9884, p-value = 8.821e-08

All factors were significant except Fastest Laps. Tried to evaluate the height factor, however, the p-value was truly not significant since the p-value was 0.895225.

The residual values are not completely normally distributed. This histogram is skewed a bit at the ends. In the normal Q-Q plot, the normality appears to be more clear because the values follow a straight line.

Data showcase 3: Fernando Alonso’s record breaking distance covered


Fernando Alonso has the most laps/distance covered in F1 Racing and so this visual demonstrates his record breaking results.

Data showcase 4: F1 WDC Racer Ages


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Data showcase 5: Drivers’ Podium Wins


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Data showcase 6: Wins per team by track since 2006


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Data showcase 7: Average Pit Stop Time from 2011-2021


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Data showcase 8: Wins per Driver since 2006


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Data showcase 9: Wins based on Started Grid Position


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Data showcase 10: 2021 Race by Race Data


Line Chart to represent Total Points in 2021 for 6 different racers

Data showcase 11: 2021 Constructor Data


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Data showcase 12: Frequency of Max Verstappen’s Finishing Points


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